


from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Features, Sequence, Value
from .base import TaskTemplate

@dataclass(frozen=snake_case__      )
class     A__   (       snake_case__      ):







    """simple docstring"""

    __magic_name__         =						field(default='question-answering-extractive'			,   metadata={'include_in_asdict_even_if_is_default': True}      )
    __magic_name__         =						Features({'question': Value('string'      ), 'context': Value('string'      )}      )
    __magic_name__         =						Features(
        {
            'answers': Sequence(
                {
                    'text': Value('string'      ),
                    'answer_start': Value('int32'      ),
                }      )
        }      )
    __magic_name__         =						"question"
    __magic_name__         =						"context"
    __magic_name__         =						"answers"
    @property
    def 						a_     (			self       ):
         return {self.question_column: "question", self.context_column: "context", self.answers_column: "answers"}








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available


_SCREAMING_SNAKE_CASE     :					Optional[int]      =       {"configuration_speech_encoder_decoder": ["SpeechEncoderDecoderConfig"]}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _SCREAMING_SNAKE_CASE     :					Optional[int]      =       ["SpeechEncoderDecoderModel"]

try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _SCREAMING_SNAKE_CASE     :					Dict      =       ["FlaxSpeechEncoderDecoderModel"]

if TYPE_CHECKING:
 from .configuration_speech_encoder_decoder import SpeechEncoderDecoderConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_speech_encoder_decoder import SpeechEncoderDecoderModel

 try:
  if not is_flax_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_flax_speech_encoder_decoder import FlaxSpeechEncoderDecoderModel

else:
 import sys

 _SCREAMING_SNAKE_CASE     :					List[Any]      =       _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




